code: def addr(input, vec1, vec2, *, beta=1, alpha=1, out=None):
      if len(ivy.shape(vec1)) != 1 or len(ivy.shape(vec2)) != 1:
          raise RuntimeError("input must be 1D vectors")
      vec1, vec2 = torch_frontend.promote_types_of_torch_inputs(
          vec1, vec2
      )
      ret = ivy.outer(vec1, vec2, out=out)
      alpha, ret = torch_frontend.promote_types_of_torch_inputs(
          alpha, ret
      )
      ret = ivy.multiply(alpha, ret, out=out)
      beta, input = torch_frontend.promote_types_of_torch_inputs(
          beta, input
      )
      beta_input = ivy.multiply(beta, input, out=out)
      beta_input, ret = torch_frontend.promote_types_of_torch_inputs(
          beta_input, ret
      )
      return ivy.add(beta_input, ret, out=out)
  
imports: import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  import ivy.functional.frontends.torch
  from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back
label_desc: Use image node_id 4 for calling a global function with example usage: addr(input, vec1, vec2) and returns: ivy